Equipment Integrity Digital Worker
This digital worker deploys a coordinated multi-agent AI system that automates the entire equipment integrity analysis workflow. Six specialized agents work in parallel to validate data, calculate corrosion rates, assess risk using API 580/581 methodology, verify compliance with industry standards, and generate prioritized recommendations with full explainability and source attribution.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
AI Mission Control - Configure and launch multi-agent equipment integrity analysis
Agent Orchestration - Real-time execution monitoring with reasoning and live findings
Analysis Results - AI-generated insights with execution flow and critical findings
Executive Summary - KPIs, ROI metrics, and risk distribution breakdown
AI Agents
Specialized autonomous agents working in coordination
Orchestrator Agent
Complex equipment analysis requires coordination of multiple specialized tasks including data validation, corrosion analysis, risk assessment, and compliance verification. Without proper orchestration, these tasks may execute in wrong order or miss dependencies.
Core Logic
The Orchestrator Agent manages the entire multi-agent workflow by decomposing the analysis mission into subtasks, assigning work to specialized agents based on their capabilities, monitoring execution progress, handling inter-agent communication, and synthesizing final results. It uses task planning algorithms to optimize execution order and minimize total processing time.
Data Validation Agent
Inspection data quality issues such as missing fields, outliers, measurement errors, and inconsistent formats can lead to incorrect analysis results and flawed maintenance decisions.
Core Logic
This agent validates input data against expected schemas, detects statistical outliers using IQR methods, verifies data completeness, and flags anomalies requiring human review. It uses schema validators, statistics engines, and outlier detection tools to ensure data integrity before downstream analysis. The agent provides data quality scores and specific warnings for problematic records.
Corrosion Analysis Agent
Engineers spend significant time manually calculating corrosion rates from thickness measurements and projecting remaining equipment life, often using spreadsheets that are prone to calculation errors and don't capture trend patterns.
Core Logic
The Corrosion Analysis Agent calculates short-term and long-term corrosion rates using linear regression on historical thickness data per API 570/510 methodologies. It performs Monte Carlo simulations for uncertainty quantification, identifies accelerating or decelerating corrosion trends, and predicts remaining equipment life with confidence intervals. All calculations include source attribution to specific TML readings.
Risk Assessment Agent
Risk-based inspection (RBI) programs require complex probability of failure (PoF) and consequence of failure (CoF) calculations that must consider multiple damage mechanisms, equipment condition, and process variables to prioritize inspection resources.
Core Logic
This agent evaluates equipment risk using API 580/581 methodology, calculating probability of failure based on damage factors, equipment condition, and inspection effectiveness. It determines consequence categories considering flammability, toxicity, and inventory volumes. Equipment is positioned on a 5x5 risk matrix with clear risk level classifications and factor breakdowns for transparency.
Compliance Agent
Maintaining compliance with API standards (510, 570, 653, 579) and regulatory requirements (OSHA PSM) requires continuous verification of inspection intervals, methodology adherence, and documentation completeness.
Core Logic
The Compliance Agent verifies inspection intervals against API requirements based on equipment type and risk level, audits calculation methodologies for standards compliance, performs gap analysis between current state and requirements, and generates compliance reports. It queries a standards database for specific regulatory requirements and flags overdue inspections.
Recommendation Agent
Converting technical analysis findings into actionable, prioritized maintenance recommendations with clear business justification is challenging. Decision-makers need cost-benefit analysis and risk reduction quantification to allocate limited resources effectively.
Core Logic
This agent synthesizes outputs from all specialist agents to generate prioritized action recommendations. It applies multi-criteria decision analysis considering risk reduction, cost-effectiveness, compliance impact, and operational feasibility. Each recommendation includes estimated cost ranges, timelines, and expected risk reduction percentages to support maintenance planning decisions.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
5 technologies
Architecture Diagram
System flow visualization